Enhanced Localization Strategy for Magnetic Capsule Robot Using On-Board Nine-Axis IMU Through Incorporation of Alternating Magnetic Field
Zhuokang Huang, You Li, Tanyong Wei, Dong Lü, Chaoyang Shi, Chengzhi Hu
- 发表年份
- 2024
- 引用次数
- 16
摘要
Capsule robots have gained increasing prominence in gastroscopy for their diagnostic capabilities and noninvasive accessibility to narrow passages with reduced risks. Magnetic positioning plays a crucial role in mapping the trajectory of the capsule robot and targeting specific areas of interest. However, the current magnetic positioning technology is limited by challenges of incompatibility with external magnetic manipulation systems, power and size constraints, and reduced resolution caused by accumulated errors during attitude estimation. Here, we propose an enhanced localization strategy for magnetic capsule robots with an on-board nine-axis inertial measurement unit (IMU) through the incorporation of an alternating magnetic field. Motion control of the capsule robot is achieved by an extracorporeal robotically manipulated permanent magnet, which also serves as a magnetic reference for determining the capsule robot’s relative position. An alternating magnetic field is applied using a single-axis Helmholtz coil to compensate for the accumulated error in the yaw angle of the IMU. A digital lock-in amplifier algorithm is employed to decouple the static magnetic field generated by the permanent magnet from the alternating magnetic fields. To improve the accuracy of attitude and position estimation, we introduce an improved magnetic dipole model, which is optimized through high-resolution spatial mapping of the magnetic field of the permanent magnet. Experimental results demonstrate that within a rectangular space of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100\times $ </tex-math></inline-formula> 100 mm, our proposed strategy achieves an average position error of 2.52 mm and an average angle error of 1.53°, meeting the accuracy requirements for clinical examinations.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002